基于优化模型补偿自抗扰的伺服控制方法研究

在永磁同步电机(PMSM)自抗扰控制器(ADRC)系统中,扩张状态观测器(ESO)在扰动较多且幅值变化大时难以保证估计精度,而普通的模型补偿自抗扰控制器的性能又受到参数辨识精度和辨识算法复杂度的限制.针对该问题,提出一种伺服系统优化的模型补偿自抗扰控制方法.以交轴电流和实际转速作为线性扩张状态观测器(LESO)输入,采用二阶LESO对系统总扰动进行观测,将此观测值作为补偿模型补偿到速度环ADRC的ESO中,并在控制量的扰动补偿项中去除该补偿模型,实现模型补偿的目的.仿真和实验结果表明,该方法显著降低了ADRC中ESO要估计量的变化幅度,提高了扰动估计精度,同时不需要进行额外的参数辨识,可实时在线获取补偿模型,具有较好的动态特性与抗扰动能力.

Research on Servo Control Method Based on Optimized Model Compensation Active Disturbance Rejection Controller

In the permanent magnet synchronous motor (PMSM) servo system controlled by active disturbance rejection controller (ADRC),the estimation accuracy of the extended state observer (ESO) is difficult to be ensured when the disturbance is more and the amplitude variation is large,and the performance of the ordinary model compensation ADRC is limited by the parameter identification precision and the complexity of identification algorithm.In order to solve this problem,an optimized model compensation ADRC for servo system is proposed.By using the second order linear extended state observer (LESO) input with the cross-axis current and the actual rotational speed,the total disturbance compensation model is obtained,which is compensated to the ADRC of speed loop and removed in the disturbance compensation term of the control quantity.Simulation and experimental results show that this method significantly reduces the variation width of the amount to be estimated by ESO and the estimation accuracy of disturbance is improved.Meanwhile,without requiring additional parameter identification,it can obtain the compensation model in real time,and has better dynamic characteristics and anti-disturbance ability.